Simulation Practice and Theory最新文献

This work presents the simulation of a two-phase flash separator, one of the processes of an industrial natural gas liquefaction plant. The model simulated was developed using the bond graph methodology, and MATLAB and 20-sim software were used to obtain the dynamic behavior of the flash. MATLAB was used to determine the input conditions of the separator as they were not provided by the plant information, and 20-sim was used to simulate the bond graph model. The simulation results were validated using real operating conditions of the plant. The paper shows how this two widely used computer programs can help in the understanding of the behavior of real process.

For many engineering systems, the mathematical model derived from a graphical model description takes the form of a system of Differential Algebraic Equations (DAEs) of index one which can be passed directly to a DAE solver. If the algebraic constraints are linear with regard to the so-called tearing variables, an alternative can be to solve them symbolically, and in that way reduce the initial DAE system into a state space model. Bond graphs well suited for a unified graphical representation of multi-disciplinary engineering systems across energy domains clearly indicate algebraic dependencies before any equations are set up. It is shown how this feature can help identify possible tearing variables and equations that determine them without having to inspect (automatically) generated model equations. Moreover, if the bond graph model is described in a modeling language like Dymola, the corresponding model processor can exploit the tearing information, solve the algebraic dependencies symbolically provided they are linear with respect to the tearing variables, and output assignment statements in a simulation language like ACSL. The proposed method is heuristic and provides a small number, not necessarily a minimal set of tearing variables. For didactic reasons, it is illustrated by means of fairly small and linear examples containing different types of algebraic dependencies. However, the method works just as well when applied to large and non-linear systems. In the latter case, tearing allows for a less costly numerical solution compared to a non-torn system.

An active or controlled system is generally composed of two parts: a passive basis and a control architecture containing actuators and sensors. When dealing with such a system, the first point usually considered is the study of the system without control. To do this, we need a model in order to get simulation-based results on the frequency domain and dynamical behaviour for dimensioning purpose. The second step is then to design a control architecture, with its actuators and sensors, specified in a way allowing the objectives to be reached as accurately and cheaply as possible. Since many years, the bond graph methodology has shown its qualities for modelling and generation of physical insight, specially when applied to multidisciplinary systems. The aim of this paper is to show how a bond graph model may be used for analysis of structural properties, i.e., properties depending only on the model structure and on the type of elements composing it, but not on the numerical values of the parameters. The properties pointed out in this way are generic, and can be used for “integrated design”, i.e., the simultaneous design of the passive system model, its control architecture and control laws for specific aims. The proposed methodology depends on causal manipulations on the bond graph model (assignment of integral and derivative causality, causal path and loops); its application may necessitate a return to the model in order to check and sometimes modify the modelling hypotheses. The proposed procedure is implemented on an example, which will be the guideline of the presentation.

In an electric battery, electric charge flows against the electric field, driven by the concentration gradient or chemical tension. Outside it flows with the electric field through the load resistor to which it supplies energy. The whole is well represented by a Bondgraph (BG) and we develop the associated equations, especially for the element SPAC (see Section 2), which affords the coupling of chemical and electric flows. So it is a case of coupled reactions, driven by the concentration gradients between the two battery compartments. The electric charge is taken in ions against its potential gradient, driven by the chemical tension or potential.

The BG has an electrical and a chemical part, connected by two elements SPAC. There is also a flow source in the chemical part, which is driven when an external current flows. The reaction proceeds between two multiport C which represent chemical effort sources and entrains the electric charge. The whole is programmed and simulated by the 20SIM program and shows the switching on and off of electric current and the gradual equalization of concentrations with depletion of the voltage: the battery is discharged.

Essential is the selective membrane, that divides two compartments with different concentrations, and lets one species of ions run through. Fuel cells are similar but have two constituents, hydrogen and oxygen, and one product, water. Other substances can be used.

This paper shows how design optimization can be achieved using signal-to-noise (S/N) ratios. A case of maintenance float policy is used to illustrate the application presented here. Basically, this involves the implementation of a robust design plan in simulation analysis. The design plan is based on the use of orthogonal arrays introduced by Taguchi. Through the application of Taguchi's S/N ratio, we demonstrate that the best design plan from an experimental design can be determined. This has several implications: (1) It reduces the experimentation time, (2) it can identify a fractional design that contains the best design plan and that design plan could be studied for full experimentation, (3) within a subset of a fractional design plan, the best design point can be found, and (4) the cost of experimentation is significantly reduced since minimal number of runs is required to identify the best design point. Finally, this important result helps experimenters to select a fractional design plan that contains the “best design point”.

An approach is introduced for semi-automatic parallelization of object-oriented simulations. The basic idea is to prepare parallelization at the earliest possible stage in the life-cycle of the creation of new simulations (i.e. at modeling), thus minimizing causality conflicts at run-time. The object-oriented model of a simulation is enriched by hints, describing the estimated load and communication costs between major classes and objects. This helps to grasp the inherent parallelism of the model. Based on this additional information, a partitioning with minimal communication between partitions can be generated automatically. Remaining dependency-conflicts must be resolved at run-time.

The GoSim [A. Stopper, GoSim, ein Ansatz zur Beschleunigung diskreter, objektorientierter, verteilter Simulationen, Ph.D. Thesis, Institute of Informatics, University Klagenfurt, 1997] simulation system is presented, which implements the described proposal and provides semi-automatic parallelization of large-scale and/or high-performance simulations. It provides a description language, a partitioning tool, a program-skeleton generator and a simulation engine. Some measurements prove the usability of the approach.

Recently, a convergence theorem of asynchronous iterations of discrete dynamic systems partitioned into blocks has been proved [2]. This theorem is verified with several asynchronous block strategies. It also generalizes the chaotic iterations. Different simulations of asynchronous evolution of discrete systems performed with the research software Discrete System Evolution (DSE), lead to the first experimental results predicted by this theorem.

The study of a particular complex system by means of computer simulation is described in this paper. Hospitals are chosen as target systems where the proposed methodology is applied. In order to choose the right decisions, hospital managers need all the information about the functioning of the organization. This research project presents a simulation tool that allows virtual societies such as hospitals to be implemented. In this way, the study of emergent behaviors in these systems can be carried out. The methodology used to model the hospital is process oriented. This approach allows us to implement a patient-centered simulation tool.

Using the parallel simulation approach is not always the best choice. There are situations in which the sequential approach works better, in terms of simulation effectiveness.

Indeed, the optimistic parallel simulation time consists of two basic components: the forward execution time, and the rollback mechanism time-overhead. It is convenient to parallelize a simulation until the latter component is not predominant with respect to the former one.

The breakeven point depends on the nature of the model to simulate, on the characteristics of the simulation platform, and on the choice of tuning parameters such as the number of processors and the checkpoint interval.

This paper deals with an evaluation of the performances of the sequential and parallel approach, in case the optimistic parallel method is used. An analytical model is introduced to study the sensitivity of the parallel simulation effectiveness to the forward event time, in case each event is rolled back no more than once.

The model is first experimentally validated and then used to determine the breakeven point between the parallel and sequential approach.

In simulation software selection problems, packages are evaluated either on their own merits or in comparison with other packages. In either method, a comprehensive list of criteria for evaluation of simulation software is essential for proper selection. Although various simulation software evaluation checklists do exist, there are differences in the lists provided and the terminologies used. This paper presents a hierarchical framework for simulation software evaluation consisting of seven main groups and several subgroups. An explanation for each criterion is provided and an analysis of the usability of the proposed framework is further discussed.